Testing a Model of Destination Image Formation: Application of Bayesian Relational Modelling and fsQCA

Fumiko Kano Glückstad*, Mikkel Nørgaard Schmidt, Morten Mørup

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Individuals’ destination images are constantly updated through their exposure to various stimuli sent from diverse information sources1 widely accessible in the modern society. Such dynamics of destination image formation2 is better explained with the iterative process of a concept learning framework integrated into the destination image models. DDIF implies that individuals having been exposed to similar stimuli in the iterative image formation process have a higher likelihood of developing a similar mental representation3. Accordingly, this study employs an innovative methodological framework to extract patterns of MR of destinations held by groups of individuals (segments) and to compare segment-specific patterns of MR with their relations to willingness to visit4 and to ISs. The results demonstrate that what segments associate with a destination relates to their W2V, and segments having rich and positive associations with a destination accessed a wider range of ISs to learn about the destination.
Original languageEnglish
JournalJournal of Business Research
Pages (from-to)351-363
Number of pages13
Publication statusPublished - Nov 2020

Bibliographical note

Published online: 25 November 2019


  • Destination image formation
  • Mental representation
  • Concept learning
  • Segmentation
  • fsQCA
  • Nonparametric Bayesian relational modeling

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